Clarify Quanto FP8 quantization
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README.md
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@@ -7,15 +7,18 @@ tags:
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- diffusers
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- fp8
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- quanto
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- text-to-image
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license: other
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license_name: openmdw1.1-license
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license_link: https://openmdw.ai/license/1-1/
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---
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# Cosmos3-Super-Text2Image FP8 Transformer
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This repository contains a transformer-only FP8/float8
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Read NVIDIA's card, license, safety notes, and prompt-format guidance here:
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[nvidia/Cosmos3-Super-Text2Image](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image).
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@@ -31,7 +34,7 @@ from diffusers import Cosmos3OmniPipeline, Cosmos3OmniTransformer
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from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler
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transformer = Cosmos3OmniTransformer.from_pretrained(
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"WaveCut/Cosmos3-Super-Text2Image-FP8-Transformer",
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subfolder="transformer",
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torch_dtype=torch.bfloat16,
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)
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- diffusers
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- fp8
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- quanto
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- optimum-quanto
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- text-to-image
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license: other
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license_name: openmdw1.1-license
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license_link: https://openmdw.ai/license/1-1/
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---
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# Cosmos3-Super-Text2Image Quanto FP8 Transformer
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This repository contains a transformer-only FP8/float8 quantization made with Hugging Face Optimum Quanto for [nvidia/Cosmos3-Super-Text2Image](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image).
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**This is a Quanto quantization, not an NVIDIA ModelOpt/NVFP quantization.** The separate NVFP experiments should be compared against this repo explicitly as a different quantization backend.
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Read NVIDIA's card, license, safety notes, and prompt-format guidance here:
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[nvidia/Cosmos3-Super-Text2Image](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image).
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from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler
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transformer = Cosmos3OmniTransformer.from_pretrained(
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"WaveCut/Cosmos3-Super-Text2Image-Quanto-FP8-Transformer",
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subfolder="transformer",
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torch_dtype=torch.bfloat16,
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)
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